CN107392382B - High-resolution geostationary orbit imaging satellite observation task planning method - Google Patents

High-resolution geostationary orbit imaging satellite observation task planning method Download PDF

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CN107392382B
CN107392382B CN201710627365.0A CN201710627365A CN107392382B CN 107392382 B CN107392382 B CN 107392382B CN 201710627365 A CN201710627365 A CN 201710627365A CN 107392382 B CN107392382 B CN 107392382B
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CN107392382A (en
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霍国清
王保伟
孔庆玲
马万权
王如双
张栋
韩续
赵超
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CETC 54 Research Institute
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Abstract

The invention discloses a high-resolution geostationary orbit imaging satellite earth observation task planning method, which designs a high-resolution geostationary orbit imaging satellite earth observation task planning method based on a genetic algorithm according to the all-time requirements of different users and considering the conflict condition of the satellite observation requirements, the imaging quality of the satellite under different illumination conditions, the satellite use constraint, the satellite swinging route and the satellite observation capability, the method comprises setting optimal observation time according to the time requirement of user observation requirement, calling genetic algorithm to arrange observation requirement based on satellite use constraint, generating observation scheme and receiving scheme, the method has the capabilities of resolving imaging requirement conflict, meeting satellite constraint, exerting the maximum potential of the satellite, optimizing the imaging path of the satellite and meeting the observation requirement of a user under the optimal illumination condition.

Description

High-resolution geostationary orbit imaging satellite observation task planning method
Technical Field
The invention relates to a high-resolution geostationary orbit imaging satellite observation task planning method, which is particularly suitable for the field of task planning of geostationary orbit imaging satellites.
Background
Geostationary orbit satellites refer to satellites that travel in a perfectly circular geosynchronous orbit perpendicular to the earth's equator, are relatively stationary with respect to the ground and are stationary above the equator. Compared with a common observation polar orbit satellite, the earth static orbit imaging satellite with high resolution at a proper quiescent point position can be used for imaging within the territorial scope of China for 24 hours, has the capabilities of rapid dynamic task planning and response, can rapidly access to sudden observation requirements, and can realize observation imaging of any position within the observation scope through satellite attitude maneuver.
The genetic algorithm is a method for effectively solving the optimal solution based on a natural genetic mechanism and natural selection. When the genetic algorithm is applied to satellite mission planning, the observation receiving schemes of each generation of group are subjected to fitness function calculation to obtain evaluation values, and necessary constraints are added, so that the observation receiving schemes can be continuously evolved towards the optimal mission planning scheme under the driving of the evaluation values, and the satellite mission planning method has the characteristics of high stability and robustness. In addition, the selection of the fitness function directly influences the evolution direction of the satellite mission planning genetic algorithm, and specific design is needed for specific application scenes.
Disclosure of Invention
The invention aims to solve the technical problem of avoiding the defects of the background technology and provides a high-resolution geostationary orbit imaging satellite earth observation task planning method based on a genetic algorithm. The method has the characteristics of giving full play to the characteristics of the geostationary orbit satellite, high demand satisfaction rate and strong robustness.
The technical problem to be solved by the invention is realized by the following technical scheme:
a high-resolution geostationary orbit imaging satellite observation task planning method comprises the following steps:
(1) acquiring observation requirements of each user, and calculating a pitching side-sway angle, a rolling side-sway angle, a pitching amplitude and a rolling amplitude of the satellite according to the geographical longitude and latitude of the observation requirements of each user and the observation mode of a target; setting optimal imaging time according to the working time period, the local time of an observation area and the running experience of the past satellite required by the observation requirements of each user;
(2) selecting a coding mode in a genetic algorithm and determining a genetic strategy, wherein the genetic strategy comprises a population size and a selection, mutation and crossing method;
(3) calling a genetic algorithm to carry out task planning according to the observation requirements of the user, and initializing randomly to generate a group;
(4) determining an idle imaging time period of each individual imaging task in a group, calculating to obtain imaging start time, imaging duration and imaging end time according to the optimal imaging time, the pitch amplitude number and the rolling amplitude number of the satellite corresponding to the imaging task in the idle imaging time period, calculating to obtain pitch side swing time and rolling side swing time according to the pitch side swing angle and the rolling side swing angle of the satellite corresponding to the previous imaging task and the next imaging task, calculating to obtain start time and stop time according to the combined on-off relation if the on-off can be combined, or calculating to obtain start time and stop time according to the pitch side swing time, the imaging mode, the imaging start time and the imaging end time; arranging a receiving time interval for each imaging task to obtain an observation scheme and a receiving scheme;
(5) respectively calculating task completion degree, priority evaluation value, satellite side-sway route evaluation value, imaging quality evaluation value and task timeliness evaluation value of each group according to a specific evaluation strategy, respectively normalizing each index to obtain a normalized value, and calculating to obtain a comprehensive evaluation value of each group according to the normalized value of each index;
(6) according to a genetic strategy, acting on the population by using a selection and crossing method, and adaptively adjusting the mutation rate of the population by using a mutation method to form a new generation population;
(7) and (4) judging whether the new generation group completes the iteration times or meets a preset index, if not, returning to the step (4), and if so, ending the process and returning to the satellite observation scheme and the satellite receiving scheme.
Wherein, the step (4) comprises the following steps:
(401) according to the imaging time requirement of each individual in the group, avoiding the imaging time period with scheduled requirements and the imaging time period which cannot be used, and acquiring all idle imaging time periods of each individual;
(402) according to the relation between all idle time periods and the optimal imaging time, sequencing all the idle time periods according to the principle that the closer the idle time periods are to the optimal imaging time, the higher the priority is;
(403) traversing all the sorted idle time periods from front to back, and taking the first idle time period as the current idle time period;
(404) when an imaging task is arranged in the current idle time period, firstly, the imaging start time is determined according to the optimal imaging time of the task, the imaging duration is calculated according to the imaging mode, the observation mode, the imaging times, the pitch amplitude number and the roll amplitude number of the satellite corresponding to the imaging task, and the imaging end time is calculated according to the imaging start time and the imaging duration;
(405) calculating the pitch side-sway angle and the rolling side-sway angle of the satellite corresponding to the front and back imaging tasks to obtain the pitch side-sway time and the rolling side-sway time, judging whether an imaging task is arranged before and after the current idle time period, if so, executing the step (406); otherwise, calculating to obtain the starting time and the shutdown time according to the pitching side-sway time, the rolling side-sway time, the imaging mode, the imaging starting time and the imaging ending time to obtain an observation scheme, and executing the step (407);
(406) judging whether the startup and shutdown can be combined or not according to the imaging mode, the data transmission mode and the imaging time interval of the front imaging task and the rear imaging task, if so, calculating to obtain the startup time and the shutdown time according to the startup and shutdown requirements after the startup and shutdown are combined, and obtaining an observation scheme; otherwise, calculating to obtain the starting time and the shutdown time according to the pitching side-sway time, the rolling side-sway time, the imaging mode, the imaging starting time and the imaging ending time to obtain an observation scheme;
(407) scheduling a receiving time interval for an imaging task to generate a receiving scheme;
(408) carrying out constraint check, and returning an observation scheme and a receiving scheme if the constraint check is passed; if not, the next idle time period is taken as the current idle time period, and the step (404) is returned until the last idle time period is selected as the current idle time period.
Wherein the step (5) is specifically as follows:
firstly, calculating according to the number of imaging tasks and the number of scheduled imaging tasks to obtain task completion; calculating according to the priority of the imaging task to obtain a priority evaluation value of the task; calculating to obtain a satellite sidesway route evaluation value of the total observation scheme according to the pitching sidesway time and rolling sidesway time of the satellite corresponding to each imaging task; determining an imaging quality evaluation value according to the relation between the actual arrangement time and the optimal imaging time of the target; calculating the timeliness evaluation value of the task according to the time difference between the receiving start time and the observation start time; normalizing each index to obtain a normalized value; and calculating to obtain a comprehensive evaluation value according to the normalized value of each index.
Compared with the mission planning method of the polar orbit satellite in the background technology, the invention has the following advantages:
1. the method fully considers the characteristics of the geostationary orbit observation satellite when the mission planning of the geostationary orbit observation satellite is carried out, and can exert the characteristics of the geostationary orbit observation satellite to the maximum extent.
The optimal observation time under the requirement of the required observation time is considered, and the imaging of the satellite under the optimal illumination condition can be effectively ensured;
2. when the mission planning of the geostationary orbit satellite is carried out, indexes such as the optimal observation time and the optimal imaging route of the satellite under the requirement of the observation mission time are considered, the task with the highest priority can be observed when the satellite carries out satellite imaging according to the established optimal imaging route, the total sidesway time is the least, the imaging quality of the task is the highest, and the observation data can be downloaded to the ground as soon as possible for application;
3. the invention has the advantages of clear and understandable logic, high stability, strong robustness and the like.
Drawings
FIG. 1 is a schematic diagram of the present invention for acquiring idle time segments during an unavailable time segment according to the prior art;
FIG. 2 is a schematic diagram of the present invention for scheduling imaging tasks according to idle time periods;
FIG. 3 is a schematic diagram of an observation scheme generated in conjunction with a power-on/off period of time in accordance with the present invention;
fig. 4 is a schematic diagram of the present invention for generating a reception scheme based on an observation scheme.
Detailed Description
The present invention will be further described with reference to fig. 1 to 4.
A high-resolution geostationary orbit imaging satellite observation task planning method comprises the following steps:
(1) acquiring observation requirements of each user, and calculating a pitching side-sway angle, a rolling side-sway angle, a pitching amplitude and a rolling amplitude of the satellite according to the geographical longitude and latitude of the observation requirements of each user and the observation mode of a target; setting optimal imaging time according to the working time period, the local time of an observation area and the running experience of the past satellite required by the observation requirements of each user;
(2) selecting a coding mode in a genetic algorithm and determining a genetic strategy, wherein the genetic strategy comprises a population size and a selection, mutation and crossing method;
(3) calling a genetic algorithm to carry out task planning according to the observation requirements of the user, and initializing randomly to generate a group;
(4) determining an idle imaging time period of each individual imaging task in a group, calculating to obtain imaging start time, imaging duration and imaging end time according to the optimal imaging time, the pitch amplitude number and the rolling amplitude number of the satellite corresponding to the imaging task in the idle imaging time period, calculating to obtain pitch side swing time and rolling side swing time according to the pitch side swing angle and the rolling side swing angle of the satellite corresponding to the front imaging task and the back imaging task, calculating to obtain the start time and the stop time according to the combined on-off relation if the on-off can be combined, or calculating to obtain the start time and the stop time according to the pitch side swing time, the rolling side swing time, the imaging mode, the imaging start time and the imaging end time; arranging a receiving time interval for each imaging task to obtain an observation scheme and a receiving scheme;
(5) respectively calculating task completion degree, priority evaluation value, satellite side-sway route evaluation value, imaging quality evaluation value and task timeliness evaluation value of each group according to a specific evaluation strategy, respectively normalizing each index to obtain a normalized value, and calculating to obtain a comprehensive evaluation value of each group according to the normalized value of each index;
(6) according to a genetic strategy, acting on the population by using a selection and crossing method, and adaptively adjusting the mutation rate to perform mutation operation to form a new generation population;
(7) and (4) judging whether the new generation group completes the iteration times or meets a preset index, if not, returning to the step (3), and if so, ending the process and returning to the optimal satellite observation scheme and receiving scheme.
When the observation scheme and the reception scheme are generated by arranging the corresponding observation reception resource for each individual demand, the following steps are specifically performed:
(401) firstly, according to the imaging time requirement of individual requirement, acquiring the imaging time interval observer with scheduled requirementi1, 2.. k, where k is the scheduled number of tasks and the unusable imaging period UselessiI is 1,2,.. m, wherein m is the number of unavailable time periods; avoiding used time period and unavailable time period to acquire idle imaging time period Uablei1, 2., n, where n is the number of idle periods, as shown in fig. 1;
(402) sorting all idle time periods according to the relation between all idle time periods and the optimal imaging time, wherein the sorting principle is that the priority is higher when the idle time periods are closer to the optimal imaging time;
(403) traversing all idle time periods from front to back within the imaging time TimeRequire requirement of the task to be scheduled, and taking the first idle time period as the current idle time period to schedule the imaging time period for the imaging task, as shown in FIG. 2;
(404) when an imaging task is arranged in the current idle time period, firstly, the imaging start time is determined in the available time period according to the optimal imaging start time of the task, the imaging duration is obtained by calculation according to the imaging mode, the observation mode, the imaging times, the pitching amplitude number and the rolling amplitude number of the satellite corresponding to the imaging task, and the imaging end time is obtained by calculation according to the imaging start time and the imaging duration;
(405) calculating the pitch side-sway angle and the rolling side-sway angle of the satellite corresponding to the front and back imaging tasks to obtain the pitch side-sway time and the rolling side-sway time, judging whether an imaging task is arranged before and after the current idle time period, if so, executing the step (406); otherwise, calculating to obtain the starting time and the shutdown time according to the pitching side-sway time, the rolling side-sway time, the imaging mode, the imaging starting time and the imaging ending time to obtain an observation scheme, and executing the step (407);
(406) judging whether the combined startup and shutdown can be carried out according to the imaging mode, the data transmission mode and the imaging time interval of the front and back observation requirements, if so, carrying out the combined startup and shutdown, and according to the combined startup and shutdown time period WorkSpaniI is 1, 2., n, where n is the number of the on/off time periods, and the pitch side-sway time, the roll side-sway time, the imaging mode, the imaging start time, and the imaging end time are calculated to obtain the on-time and the off-time, so as to obtain the observation scheme, as shown in fig. 3;
(407) scheduling a receiving period for each observation task, and generating a receiving scheme, as shown in fig. 4;
(408) and (5) checking the observation scheme and the receiving scheme according to the satellite use constraint, if the constraint is not met, continuing to the step (3), and if the constraint is met, returning to the observation scheme and the receiving scheme. The observation scheme comprises imaging start time, imaging end time and on-off time.
When the comprehensive evaluation value of each group is calculated by the fitness function, the following are specific:
1) and calculating to obtain task Completion degree Completion according to the total number of the observation targets and the number of the arranged tasks:
for observation requirements proposed by different users, due to time conflicts and satellite constraints, the finally generated observation scheme may not meet all requirements of all users, so that the task completion degree can be obtained by counting the ratio of the number of scheduled tasks to the total number of tasks:
Figure GDA0002284831870000081
wherein, Number represents the total Number of the observation targets; the Mission indicates the number of scheduled observation targets.
2) Calculating the Priority evaluation value Priority of the task according to the Priority of the task:
since each task is set with priority according to the degree of urgency, when the more tasks with high priority are scheduled, the higher the task priority, the greater the overall profit value.
Figure GDA0002284831870000091
Wherein Number represents the total Number of scheduled targets; priorityjIndicating the priority of the jth target; max is the maximum value of the priority, wherein a smaller priority indicates a higher urgency for the task.
3) Calculating to obtain a total sidesway evaluation value Path with the minimum total sidesway time according to the total sidesway time of each task:
Figure GDA0002284831870000092
wherein Number represents the total Number of targets; the MaxSwayTime is the maximum yaw time and comprises pitch yaw time and roll yaw time; SwayTimejIndicating the roll time of the jth target, and when the jth target is not scheduled, it is MaxSwayTime.
4) Determining an imaging Quality evaluation value Quality according to the relation between the actual arrangement time and the optimal imaging time of the target:
when the accurate imaging starting time is selected by the required target, the ideal imaging starting time is the imaging starting time set by the user; when the user sets only the imaging period, the time at which the optimum lighting condition is found within the imaging period is set as the ideal imaging time, and the closer the actual imaging time at which the task is scheduled is to the ideal imaging time, the higher the imaging quality.
Figure GDA0002284831870000093
Wherein Number represents the total Number of scheduled tasks; observetimejA scheduled actual imaging time representing the jth observation task; ideal timejThe optimal imaging time for the jth observation task.
5) Calculating the timeliness evaluation value Ungency of the task according to the time difference between the receiving start time and the observation start time:
the closer the reception start time is to the imaging start time, the higher the efficiency of the task's compliance.
Figure GDA0002284831870000101
Wherein Number represents the total Number of scheduled tasks; observetimejA scheduled actual imaging time representing the jth observation task; receiveTimejIs the reception start time of the jth observation task.
6) Normalizing each index to obtain Basei
Since the dimensions of each index are different, in order to perform unified processing on each index, normalization processing is performed on each index first. For a positive indicator, i.e., the greater the value, the greater the gain, the normalization formula is
Figure GDA0002284831870000102
For the inverse index, i.e., the larger the value the smaller the benefit, the normalized formula is
Figure GDA0002284831870000103
Wherein the content of the first and second substances,
Figure GDA0002284831870000104
is the jth index of the ith target.
7) Calculating to obtain a comprehensive evaluation value according to the normalized value of each index,
Figure GDA0002284831870000105
wherein, BaseiNormalized value of the ith index; omegaiIs the weight of the ith index.
And finishing the earth stationary orbit imaging satellite earth observation task planning.

Claims (3)

1. A high-resolution geostationary orbit imaging satellite observation task planning method is characterized by comprising the following steps:
(1) acquiring observation requirements of each user, and calculating a pitching side-sway angle, a rolling side-sway angle, a pitching amplitude and a rolling amplitude of the satellite according to the geographical longitude and latitude of the observation requirements of each user and the observation mode of a target; setting optimal imaging time according to the working time period, the local time of an observation area and the running experience of the past satellite required by the observation requirements of each user;
(2) selecting a coding mode in a genetic algorithm and determining a genetic strategy, wherein the genetic strategy comprises a population size and a selection, mutation and crossing method;
(3) calling a genetic algorithm to carry out task planning according to the observation requirements of the user, and initializing randomly to generate a group;
(4) determining an idle imaging time period of each individual imaging task in a group, calculating to obtain imaging start time, imaging duration and imaging end time according to the optimal imaging time, the pitch amplitude number and the rolling amplitude number of the satellite corresponding to the imaging task in the idle imaging time period, calculating to obtain pitch side swing time and rolling side swing time according to the pitch side swing angle and the rolling side swing angle of the satellite corresponding to the previous imaging task and the next imaging task, calculating to obtain start time and stop time according to the combined on-off relation if the on-off can be combined, or calculating to obtain start time and stop time according to the pitch side swing time, the imaging mode, the imaging start time and the imaging end time; arranging a receiving time interval for each imaging task to obtain an observation scheme and a receiving scheme;
(5) respectively calculating task completion degree, priority evaluation value, satellite side-sway route evaluation value, imaging quality evaluation value and task timeliness evaluation value of each group according to a specific evaluation strategy, respectively normalizing each index to obtain a normalized value, and calculating to obtain a comprehensive evaluation value of each group according to the normalized value of each index;
(6) according to a genetic strategy, acting on the population by using a selection and crossing method, and adaptively adjusting the mutation rate of the population by using a mutation method to form a new generation population;
(7) and (4) judging whether the new generation group completes the iteration times or meets a preset index, if not, returning to the step (4), and if so, ending the process and returning to the satellite observation scheme and the satellite receiving scheme.
2. The method of claim 1, wherein the method comprises: the step (4) specifically comprises the following steps:
(401) according to the imaging time requirement of each individual in the group, avoiding the imaging time period with scheduled requirements and the imaging time period which cannot be used, and acquiring all idle imaging time periods of each individual;
(402) according to the relation between all idle time periods and the optimal imaging time, sequencing all the idle time periods according to the principle that the closer the idle time periods are to the optimal imaging time, the higher the priority is;
(403) traversing all the sorted idle time periods from front to back, and taking the first idle time period as the current idle time period;
(404) when an imaging task is arranged in the current idle time period, firstly, the imaging start time is determined according to the optimal imaging time of the task, the imaging duration is calculated according to the imaging mode, the observation mode, the imaging times, the pitch amplitude number and the roll amplitude number of the satellite corresponding to the imaging task, and the imaging end time is calculated according to the imaging start time and the imaging duration;
(405) calculating the pitch side-sway angle and the rolling side-sway angle of the satellite corresponding to the front and back imaging tasks to obtain the pitch side-sway time and the rolling side-sway time, judging whether an imaging task is arranged before and after the current idle time period, if so, executing the step (406); otherwise, calculating to obtain the starting time and the shutdown time according to the pitching side-sway time, the rolling side-sway time, the imaging mode, the imaging starting time and the imaging ending time to obtain an observation scheme, and executing the step (407);
(406) judging whether the startup and shutdown can be combined or not according to the imaging mode, the data transmission mode and the imaging time interval of the front imaging task and the rear imaging task, if so, calculating to obtain the startup time and the shutdown time according to the startup and shutdown requirements after the startup and shutdown are combined, and obtaining an observation scheme; otherwise, calculating to obtain the starting time and the shutdown time according to the pitching side-sway time, the rolling side-sway time, the imaging mode, the imaging starting time and the imaging ending time to obtain an observation scheme;
(407) scheduling a receiving time interval for an imaging task to generate a receiving scheme;
(408) carrying out constraint check, and returning an observation scheme and a receiving scheme if the constraint check is passed; if not, the next idle time period is taken as the current idle time period, and the step (404) is returned until the last idle time period is selected as the current idle time period.
3. The method of claim 1, wherein the method comprises: the step (5) is specifically as follows:
firstly, calculating according to the number of imaging tasks and the number of scheduled imaging tasks to obtain task completion; calculating according to the priority of the imaging task to obtain a priority evaluation value of the task; calculating to obtain a satellite sidesway route evaluation value of the total observation scheme according to the pitching sidesway time and rolling sidesway time of the satellite corresponding to each imaging task; determining an imaging quality evaluation value according to the relation between the actual arrangement time and the optimal imaging time of the target; calculating the timeliness evaluation value of the task according to the time difference between the receiving start time and the observation start time; normalizing each index to obtain a normalized value; and calculating to obtain a comprehensive evaluation value according to the normalized value of each index.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2143640B1 (en) * 2008-07-10 2011-09-07 Astrium Sas Method for the launch, station acquisition and station-keeping of a satellite in GEO orbit
CN103093098A (en) * 2013-01-21 2013-05-08 武汉大学 Quantitative evaluation method of satellite optical sensor dynamic observation ability
CN105426964A (en) * 2015-11-03 2016-03-23 合肥工业大学 Joint task planning method for satellite imaging and transmission
CN105512479A (en) * 2015-12-03 2016-04-20 中国地质大学(武汉) Evaluation method and device of multi-satellite earth observation task planning algorithms
CN105654220A (en) * 2014-11-27 2016-06-08 航天恒星科技有限公司 Multi-satellite combined observation method and system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2143640B1 (en) * 2008-07-10 2011-09-07 Astrium Sas Method for the launch, station acquisition and station-keeping of a satellite in GEO orbit
CN103093098A (en) * 2013-01-21 2013-05-08 武汉大学 Quantitative evaluation method of satellite optical sensor dynamic observation ability
CN105654220A (en) * 2014-11-27 2016-06-08 航天恒星科技有限公司 Multi-satellite combined observation method and system
CN105426964A (en) * 2015-11-03 2016-03-23 合肥工业大学 Joint task planning method for satellite imaging and transmission
CN105512479A (en) * 2015-12-03 2016-04-20 中国地质大学(武汉) Evaluation method and device of multi-satellite earth observation task planning algorithms

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Satellite Observing Mission Scheduling Method;Chen Wang;《2016 IEEE 28th International Conference on Tools with Artificial Intelligence》;20170116;全文 *
刘嵩等.敏捷成像卫星时间依赖型调度问题、模型与算法.《系统工程理论与实践》.2016,第36卷(第3期), *
鲁棒性资源调度方法及其在卫星任务规划中的应用;张弛;《中国优秀硕士学位论文全文数据库工程科技II辑》;20120215;全文 *

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